Different mechanisms for modulation of the initiation and steady-state of smooth pursuit eye movements

Abstract

Smooth pursuit eye movements are used by primates to track moving objects. They are initiated by sensory estimates of target speed represented in the middle temporal (MT) area of extrastriate visual cortex and then supported by motor feedback to maintain steady-state eye speed at target speed. Here, we show that reducing the coherence in a patch of dots for a tracking target degrades the eye speed both at the initiation of pursuit and during steady-state tracking, when eye speed reaches an asymptote well below target speed. The deficits are quantitatively different between the motor-supported steady-state of pursuit and the sensory-driven initiation of pursuit, suggesting separate mechanisms. The deficit in visually guided pursuit initiation could not explain the deficit in steady-state tracking. Pulses of target speed during steady-state tracking revealed lower sensitivities to image motion across the retina for lower values of dot coherence. However, sensitivity was not zero, implying that visual motion should still be driving eye velocity toward target velocity. When we changed dot coherence from 100% to lower values during accurate steady-state pursuit, we observed larger eye decelerations for lower coherences, as expected if motor feedback was reduced in gain. A simple pursuit model accounts for our data based on separate modulation of the strength of visual-motor transmission and motor feedback. We suggest that reduced dot coherence allows us to observe evidence for separate modulations of the gain of visual-motor transmission during pursuit initiation and of the motor corollary discharges that comprise eye velocity memory and support steady-state tracking.NEW & NOTEWORTHY We exploit low-coherence patches of dots to control the initiation and steady state of smooth pursuit eye movements and show that these two phases of movement are modulated separately by the reliability of visual motion signals. We conclude that the neural circuit for pursuit includes separate modulation of the strength of visual-motor transmission for movement initiation and of eye velocity positive feedback to support steady-state tracking.

Keywords: cerebellum; floccular complex; gain modulation; motion reliability; velocity memory; visual motion.

Fig. 1.

Stimulus and behavioral paradigm. A: the 3 patches of dots show the motion of dots within patches that have 100%, 50%, or 0% coherence. B: the schematic shows the trial structure. Each trial begins with fixation before moving through brief local motion of the dots within an invisible stationary aperture and global, en bloc motion of the dots and the aperture to a fixation stationary stimulus for fixation and reward. The same dot coherence was retained during the periods of both local and global motion. After the start of global motion, the target can continue unaltered (no pulse) or can undergo either a brief pulse of either dot coherence or stimulus speed.

Fig. 2.

Effect of dot coherence on the initiation of pursuit and steady-state tracking. Average eye speed as a function of time for an example session in each of the 2 monkeys. A and C: data for the first 200 ms after the onset of target motion at 10°/s. B and D: data for the entire response to target motion, extending the example eye speed traces in A and C. The vertical dashed line marks 200 ms after the onset of target motion, where the traces in A and C end. The gaps in the eye speed traces indicate intervals when over half of trials used in the averages contained saccades. In A–D, the transition of colors from bright green to black indicates data for patches of dots moving with 100% to 0% coherence. E and F: relative eye speed of data in A–D is plotted as a function of motion coherence. Error bars represent means ± SD across individual responses for a representative experiment in each monkey.

Fig. 3.

Quantitative comparison of the effects of dot coherence on the initiation versus the steady-state of pursuit. A: relative eye speed is plotted as a function of motion coherence for steady-state tracking and the initiation of pursuit. B: relative eye speed during steady-state tracking is plotted as a function of that during the initiation of pursuit for different values of dot coherence. The dashed line has a slope of one. In A and B, different colors show data for the 2 monkeys at 2 speeds. Data were normalized to have a value of 1 for motion coherence of 100% in each session and then averaged across sessions. Error bars are means ± SE for n = 4 experiments (monkey R, 10°/s), n = 6 experiments (monkey X, 10°/s), n = 10 experiments (monkey R, 20°/s), and n = 10 experiments (monkey X, 20°/s).

Fig. 4.

Effect of changing the prior for target speed on the eye speeds for low versus high coherence patches of dots. The 3 graphs at right show the mix of target speeds in each of the contexts used to control the speed prior. A and B: averages of eye speed as a function of time from an example experiment in 1 monkey showing the initiation of pursuit (A) and steady-state tracking (B) for 100% and 10% coherence motion. Different colors show data for different speed contexts. The pink shading highlights the interval when eye speeds were analyzed. Gaps in the eye speed traces show the intervals when over half of the trials had saccades. C–F: relative eye speeds for high coherence versus low coherence dots during pursuit initiation (C and D) and steady-state tracking (E and F). Dotted lines have slopes of 1. Green and blue symbols show data for the slow and fast context, respectively. Each experimental day contributed a pair of symbols showing averages across at least 10 full cycles of slow, fast, and control contexts. All data are normalized for eye speeds during the control contexts.

Fig. 5.

Example eye speed traces for speed and coherence pulses from different starting conditions. Gray shading indicates the duration of the pulses. A and B: speed pulses that increased or decreased target speed from starting conditions of target motion at 10°/s and motion coherence of 100% (A) or 10% (B). In A and B, 2 of the traces show average eye speeds for speed pulses from 10 to 14 or 6°/s and that other 3 traces show average eye speeds for sustained target motion at 6, 10, or 14°/s. C–F: coherence pulses that either increased coherence (C and D) from 0% or 20% to 100% or decreased coherence (E and F) from 100% to 20% or 0%. Different colors indicate different starting conditions and pulses. In C, D, E, and F, 1 trace shows the average eye speed for a given coherence pulse and the other 2 traces show the average eye speeds for unperturbed target motions with the 2 coherences used in C, D, E, and F. Shaded ribbons around the traces represent means ± SE; n = 14 experiments for 100% coherence and 10°/s; n = 12 for 100% coherence and 10→14°/s and 10→6°/s; n = 9 for 100% coherence and 14°/s and 6°/s; n = 7 for 10% coherence and 10°/s, 10→14°/s, 10→6°/s, 14°/s, and 6°/s; n = 4 for 10°/s and 100%, 20%, and 0% coherence; and n = 2 for 10°/s and 0→100%, 20→100%, 100→0%, and 100→20% coherence.

Fig. 6.

Sensitivity to image motion during deficient steady-state tracking induced by reduced dot coherence. A: target speed trajectories for presentation of speed pulses. B and C: average eye speeds for target speed pulses during steady-state pursuit with target coherences of 100% and 20%, respectively. The gray shading highlights the time of the speed pulse, and the pink shading highlights the first 75 ms of the eye response used for analysis. D and E: the first 75 ms of eye acceleration plotted as a function of the image speed before the beginning of the eye response for 2 monkeys. The lines show regression fits and the dotted lines represent 95% confidence intervals. F and G: the slope of each fit plotted as a function of dot coherence. Error bars represent 95% confidence intervals. For monkey X, we presented speed pulses during pursuit with 20% coherence (n = 12 for ± 4°/s, n = 10 for ± 2°/s, and n = 14 for 0°/s); 30% coherence (n = 12 for all speeds); 40% coherence (n = 6 for all speeds); 50% coherence (n = 6 for all speeds); 60% coherence (n = 6 for ± 4°/s, n = 4 for ± 2°/s, and n = 8 for 0°/s); 70% coherence (n = 6 for all speeds); and 100% coherence (n = 20 for ± 4°/s, n = 18 for ± 2°/s, and n = 26 for 0°/s). For monkey R, we used 10% coherence (n = 3 for ± 8°/s, n = 7 for ± 4°/s, n = 4 for ± 2°/s, and n = 14 for 0°/s); 20% coherence (n = 8 for ± 8°/s, n = 12 for ± 4°/s, n = 9 for ± 2°/s, n = 4 for ± 1°/s, and n = 28 for 0°/s); 30% coherence (n = 3 for ± 8°/s, n = 7 for ± 4°/s, n = 4 for ± 2°/s, and n = 14 for 0°/s); 60% coherence (n = 8 for ± 8°/s, n = 12 for ± 4°/s, n = 9 for ± 2°/s, n = 4 for ± 1°/s, and n = 28 for 0°/s); and 100% coherence (n = 8 for ± 8°/s, n = 12 for ± 4°/s, n = 9 for ± 2°/s, n = 4 for ± 1°/s, and n = 28 for 0°/s).

Fig. 7.

Effect of changes in motion coherence during steady-state tracking. A: trajectory of target coherences. B: eye speed responses to changes in coherence for 1 monkey. The gray shading indicates the interval when the target coherence was reduced and the pink shading shows the first 75 ms of the eye response used for analysis. The lighter ribbon around each trace represents the standard error of the mean for n = 6 experiments for each condition. The dotted line marks 300 ms after coherence change, the time when coherence pulses seen in Fig. 5 would have ended. C and D: average eye accelerations from the first 75 ms of the eye response plotted as a function of target coherence at the end of the trial. Error bars are means ± SE. For monkey R: n = 6 experiments for 100→10%, 100→30%, 100→50%, 100→70%, 100→80%, and 100→90% coherence; and n = 10 for 100→0%, 100→20%, 100→40%, 100→60%, and 100% coherence. For monkey X: n = 8 experiments for 100→10%, 100→30%, 100→50%, 100→70%, 100→80%, and 100→90% coherence; and n = 14 for 100→0%, 100→20%, 100→40%, 100→60%, and 100% coherence.

Fig. 8.

Predictions of a computational model of pursuit behavior showing the effects of changes in gain at 2 different sites. The schematic at the top shows the model, and the red arrows indicate the 2 sites of gain modulation by dot coherence. The model terms g₁ and g₂ controlled the gain of visual-motor transmission and the gain of eye velocity positive feedback, respectively. A–C: simulated eye speeds to pursuit of targets with high to low coherence, where different colored traces indicate simulations based on data from different values of motion coherence. The values of g₁ and g₂ were changed either together (A) or individually (B and C).